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Spatial Intelligence Jobs (NOW HIRING)

Vantor

Sr. Platform Infrastructure Engineer

Westminster, CO · On-site

$109K - $148K/yr

Vantor is forging the new frontier of spatial intelligence, helping decision makers and operators navigate what's happening now and shape what's coming next. Vantor is a place for problem solvers ...

Amazon

Applied Scientist, Fauna

Sunnyvale, CA · On-site

We are seeking an Applied Scientist to focus on Robotics Spatial Intelligence and Semantic Understanding. In this role, you'll research and build advanced semantic and world understanding algorithms ...

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How much do spatial intelligence jobs pay per year?

As of Sep 4, 2026, the average yearly pay for spatial intelligence in the United States is $100,573.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,500.00 and $132,500.00 per year, depending on experience, location, and employer.

What is spatial intelligence?

A Spatial Intelligence job involves analyzing and interpreting spatial data to identify patterns, trends, and relationships in geographic or built environments. Professionals in this field use GIS (Geographic Information Systems), remote sensing, and data visualization tools to support decision-making in industries like urban planning, logistics, environmental management, and defense. They help organizations optimize resources, improve efficiency, and solve complex spatial problems. Strong analytical skills, proficiency in mapping software, and an understanding of spatial relationships are essential for success in this role.

What does someone in spatial intelligence do?

Professionals in Spatial Intelligence often work on projects involving spatial data analysis, mapping, and the creation of geospatial models to support organizational decision-making. Their responsibilities may include collecting and processing geographic data, conducting site suitability analyses, performing spatial risk assessments, and generating detailed maps or visual reports for stakeholders. They typically collaborate with urban planners, engineers, data scientists, and decision-makers to integrate spatial perspectives into broader business strategies. day can vary between intensive data analysis, meeting with project teams, and presenting findings to clients or leadership. This dynamic role offers the opportunity to make significant impacts on projects such as urban development, environmental conservation, and transportation planning.

What are the key skills and qualifications needed for spatial intelligence?

To excel in a Spatial Intelligence role, individuals typically need a strong background in geospatial analysis, GIS (Geographic Information Systems), and spatial data interpretation, often supported by a degree in geography, urban planning, data science, or a related field. Familiarity with specialized software such as ArcGIS, QGIS, remote sensing tools, and spatial databases is essential, and certifications in GIS or remote sensing are highly valued. Strong analytical thinking, attention to detail, and effective communication are important soft skills for translating complex spatial data into actionable insights. These skills ensure the professional can deliver accurate spatial analyses that inform decision-making across industries such as urban planning, environmental management, and logistics.

Is geospatial intelligence a good career?

Geospatial intelligence is a growing field that involves analyzing geographic data using tools like GIS and remote sensing. It offers opportunities in government, defense, and private sectors, often requiring technical skills and security clearances. The career can be stable and rewarding for those interested in spatial analysis and technology.

What careers use spatial intelligence?

Careers that utilize spatial intelligence include architecture, engineering, urban planning, surveying, and graphic design. These roles often require strong visualization skills, proficiency with design software, and the ability to interpret spatial data and diagrams.
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Spatial Intelligence jobs near you
Infographic showing various Spatial Intelligence job openings in the United States as of August 2026, with employment types broken down into 89% Full Time, 8% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $100,573 per year, or $48.4 per hour.

Lead AI / ML Staff Engineer

Dream Technologies Inc

San Francisco, CA • On-site

$120K - $159K/yr

Full-time

Re-posted 17 days ago

Job description

We are looking for a Lead AI & Algorithms Engineer to own the full lifecycle of novel spatial model development; defining the right framing of complex inference problems, structuring image, video, and vectorized floorplan data into usable training formats, training and evaluating models, and deploying performant systems into our production stack. You'll be responsible for developing and advancing our diffusion models and 3D generative models that power Dream's core spatial intelligence.
Upcoming Challenges
  • Create training datasets from imperfect sources (LiDAR Scans, scraped construction docs)
  • Combining heuristics, labeling tools, and clever preprocessing (e.g. object detection models) to generate high-quality data at scale.
  • Design and train novel spatial deep learning models that intelligently infer room layouts, surface boundaries, and object placement from partial inputs - balancing architectural plausibility with flexibility and precision.
  • Explore hybrid approaches that combine classical geometry algorithms with learned models.
  • Benchmark and iterate on model performance across multiple axes - accuracy, speed, generalization
  • Integrate AI models directly into the product stack, working closely with full-stack engineers to ensure outputs are usable in the interactive 3D design environment.

What we Require
  • 4+ Years of experience training and deploying real-world AI . Deep understanding of model architectures, training pipelines, and evaluation methodologies.
  • Creativity and technical depth to explore, evaluate, and iterate on different algorithmic approaches.
  • Scrappiness and speed in turning unstructured or incomplete data into usable training sets, and in getting models built and tested under real constraints.
  • Strong background in algorithms and data structures, with the ability to design performant solutions to spatial and generative problems.
  • Hands-on experience with procedural generation techniques, especially in the context of 3D geometry, modeling, or simulation.
  • Expert proficiency in Python, with a strong preference for experience using static typing (e.g., with type hints, MyPy, or Pydantic).

Apply